Knowledge discovery in scientific databases using text mining and social network analysis

Abstract

This paper introduces a novel methodology to extract core concepts from text corpus. This methodology is based on text mining and social network analysis. At the text mining phase the keywords are extracted by tokenizing, removing stop-lists and generating N-grams. Network analysis phase includes co-word occurrence extraction, network representation of linked terms and calculating centrality measure. We applied our methodology on a text corpus including 650 thesis titles in the domain of Industrial engineering. Interpreting enriched networks was interesting and gave us valuable knowledge about corpus content.